Brain organoids represent a powerful tool for studying human neurological diseases, particularly those that affect brain growth and structure. However, many diseases manifest with clear evidence of physiological and network abnormality in the absence of anatomical changes, raising the question of whether organoids possess sufficient neural network complexity to model these conditions. Here, we explore the network-level functions of brain organoids using calcium sensor imaging and extracellular recording approaches that together reveal the existence of complex network dynamics reminiscent of intact brain preparations. We demonstrate highly abnormal and epileptiform-like activity in organoids derived from induced pluripotent stem cells from individuals with Rett syndrome, accompanied by transcriptomic differences revealed by single-cell analyses. We also rescue key physiological activities with an unconventional neuroregulatory drug, pifithrin-α. Together, these findings provide an essential foundation for the utilization of brain organoids to study intact and disordered human brain network formation and illustrate their utility in therapeutic discovery.
Subscribe to Journal
Get full journal access for 1 year
only $4.92 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Tax calculation will be finalised during checkout.
Rent or Buy article
Get time limited or full article access on ReadCube.
All prices are NET prices.
Raw and processed scRNA-seq data were deposited at the Gene Expression Omnibus under accession number GSE165577. The authors declare that all other data supporting the findings of this study are available within the paper and its Supplementary Information files.
Di Lullo, E. & Kriegstein, A. R. The use of brain organoids to investigate neural development and disease. Nat. Rev. Neurosci. 18, 573–584 (2017).
Amin, N. D. & Pasca, S. P. Building models of brain disorders with three-dimensional organoids. Neuron 100, 389–405 (2018).
Qian, X., Song, H. & Ming, G. L. Brain organoids: advances, applications and challenges. Development 146, dev166074 (2019).
Rakic, P. Evolution of the neocortex: a perspective from developmental biology. Nat. Rev. Neurosci. 10, 724–735 (2009).
Molnar, Z. et al. Evolution and development of the mammalian cerebral cortex. Brain Behav. Evol. 83, 126–139 (2014).
van der Worp, H. B. et al. Can animal models of disease reliably inform human studies? PLoS Med. 7, e1000245 (2010).
Dawson, T. M., Golde, T. E. & Lagier-Tourenne, C. Animal models of neurodegenerative diseases. Nat. Neurosci. 21, 1370–1379 (2018).
Stam, C. J. Modern network science of neurological disorders. Nat. Rev. Neurosci. 15, 683–695 (2014).
Palop, J. J. & Mucke, L. Network abnormalities and interneuron dysfunction in Alzheimer disease. Nat. Rev. Neurosci. 17, 777–792 (2016).
Sun, A. X. et al. Potassium channel dysfunction in human neuronal models of Angelman syndrome. Science 366, 1486–1492 (2019).
Trujillo, C. A. et al. Complex oscillatory waves emerging from cortical organoids model early human brain network development. Cell Stem Cell 25, 558–569 (2019).
Buzsaki, G. & Wang, X. J. Mechanisms of gamma oscillations. Annu Rev. Neurosci. 35, 203–225 (2012).
Headley, D. B. & Paré, D. Common oscillatory mechanisms across multiple memory systems. NPJ Sci. Learn. 2, 1 (2017).
Verret, L. et al. Inhibitory interneuron deficit links altered network activity and cognitive dysfunction in Alzheimer model. Cell 149, 708–721 (2012).
Matsumoto, J. Y. et al. Network oscillations modulate interictal epileptiform spike rate during human memory. Brain 136, 2444–2456 (2013).
van Dellen, E. et al. Local polymorphic delta activity in cortical lesions causes global decreases in functional connectivity. Neuroimage 83, 524–532 (2013).
Watanabe, M. et al. Self-organized cerebral organoids with human-specific features predict effective drugs to combat Zika virus infection. Cell Rep. 21, 517–532 (2017).
Bagley, J. A., Reumann, D., Bian, S., Levi-Strauss, J. & Knoblich, J. A. Fused cerebral organoids model interactions between brain regions. Nat. Methods 14, 743–751 (2017).
Birey, F. et al. Assembly of functionally integrated human forebrain spheroids. Nature 545, 54–59 (2017).
Xiang, Y. et al. Fusion of regionally specified hPSC-derived organoids models human brain development and interneuron migration. Cell Stem Cell 21, 383–398 (2017).
Sakaguchi, H., et al. Self-organized synchronous calcium transients in a cultured human neural network derived from cerebral organoids. Stem Cell Reports 13, 458–473 (2019).
Lyst, M. J. & Bird, A. Rett syndrome: a complex disorder with simple roots. Nat. Rev. Genet. 16, 261–275 (2015).
Garofalo, E. A., Drury, I. & Goldstein, G. W. EEG abnormalities aid diagnosis of Rett syndrome. Pediatr. Neurol. 4, 350–353 (1988).
Operto, F. F., Mazza, R., Pastorino, G. M. G., Verrotti, A. & Coppola, G. Epilepsy and genetic in Rett syndrome: a review. Brain Behav. 9, e01250 (2019).
Watanabe, M., et al. TGFβ superfamily signaling regulates the state of human stem cell pluripotency and competency to create telencephalic organoids. Preprint at bioRxiv, https://doi.org/10.1101/2019.12.13.875773 (2019).
Hendry, S. H., Schwark, H. D., Jones, E. G. & Yan, J. Numbers and proportions of GABA-immunoreactive neurons in different areas of monkey cerebral cortex. J. Neurosci. 7, 1503–1519 (1987).
Sahara, S., Yanagawa, Y., O’Leary, D. D. & Stevens, C. F. The fraction of cortical GABAergic neurons is constant from near the start of cortical neurogenesis to adulthood. J. Neurosci. 32, 4755–4761 (2012).
Ferando, I. & Mody, I. In vitro gamma oscillations following partial and complete ablation of delta subunit-containing GABAA receptors from parvalbumin interneurons. Neuropharmacology 88, 91–98 (2015).
Pnevmatikakis, E. A. et al. Simultaneous denoising, deconvolution and demixing of calcium imaging data. Neuron 89, 285–299 (2016).
Zhou, P., et al. Efficient and accurate extraction of in vivo calcium signals from microendoscopic video data. Elife 7, e28728 (2018).
Buzsaki, G. & Draguhn, A. Neuronal oscillations in cortical networks. Science 304, 1926–1929 (2004).
Wang, D. D. & Kriegstein, A. R. GABA regulates excitatory synapse formation in the neocortex via NMDA receptor activation. J. Neurosci. 28, 5547–5558 (2008).
Wang, D. D. & Kriegstein, A. R. Blocking early GABA depolarization with bumetanide results in permanent alterations in cortical circuits and sensorimotor gating deficits. Cereb. Cortex 21, 574–587 (2011).
Leonard, H., Cobb, S. & Downs, J. Clinical and biological progress over 50 years in Rett syndrome. Nat. Rev. Neurol. 13, 37–51 (2017).
Mellios, N. et al. MeCP2-regulated miRNAs control early human neurogenesis through differential effects on ERK and AKT signaling. Mol. Psychiatry 23, 1051–1065 (2018).
Armstrong, D. D., Dunn, K. & Antalffy, B. Decreased dendritic branching in frontal, motor and limbic cortex in Rett syndrome compared with trisomy 21. J. Neuropathol. Exp. Neurol. 57, 1013–1017 (1998).
Belichenko, P. V. et al. Widespread changes in dendritic and axonal morphology in Mecp2-mutant mouse models of Rett syndrome: evidence for disruption of neuronal networks. J. Comp. Neurol. 514, 240–258 (2009).
Marchetto, M. C. et al. A model for neural development and treatment of Rett syndrome using human induced pluripotent stem cells. Cell 143, 527–539 (2010).
Ohashi, M. et al. Loss of MECP2 leads to activation of P53 and neuronal senescence. Stem Cell Reports 10, 1453–1463 (2018).
D’Haene, E. et al. A neuronal enhancer network upstream of MEF2C is compromised in patients with Rett-like characteristics. Hum. Mol. Genet. 28, 818–827 (2019).
Wang, J. et al. Novel MEF2C point mutations in Chinese patients with Rett (-like) syndrome or non-syndromic intellectual disability: insights into genotype-phenotype correlation. BMC Med. Genet. 19, 191 (2018).
Salpietro, V. et al. AMPA receptor GluA2 subunit defects are a cause of neurodevelopmental disorders. Nat. Commun. 10, 3094 (2019).
Huisman, S. et al. Phenotypes and genotypes in individuals with SMC1A variants. Am. J. Med. Genet. A 173, 2108–2125 (2017).
Lopes, F. et al. Identification of novel genetic causes of Rett syndrome-like phenotypes. J. Med. Genet. 53, 190–199 (2016).
Oyang, E. L., Davidson, B. C., Lee, W. & Poon, M. M. Functional characterization of the dendritically localized mRNA neuronatin in hippocampal neurons. PLoS ONE 6, e24879 (2011).
Sharma, J. et al. Neuronatin-mediated aberrant calcium signaling and endoplasmic reticulum stress underlie neuropathology in Lafora disease. J. Biol. Chem. 288, 9482–9490 (2013).
Lu, H. et al. Loss and gain of MeCP2 cause similar hippocampal circuit dysfunction that is rescued by deep brain stimulation in a Rett syndrome mouse model. Neuron 91, 739–747 (2016).
Feldt Muldoon, S., Soltesz, I. & Cossart, R. Spatially clustered neuronal assemblies comprise the microstructure of synchrony in chronically epileptic networks. Proc. Natl Acad. Sci. USA 110, 3567–3572 (2013).
Bragin, A., Engel, J. Jr., Wilson, C. L., Fried, I. & Buzsaki, G. High-frequency oscillations in human brain. Hippocampus 9, 137–142 (1999).
Bragin, A., Wilson, C. L., Almajano, J., Mody, I. & Engel, J. Jr. High-frequency oscillations after status epilepticus: epileptogenesis and seizure genesis. Epilepsia 45, 1017–1023 (2004).
Ito-Ishida, A., Ure, K., Chen, H., Swann, J. W. & Zoghbi, H. Y. Loss of MeCP2 in parvalbumin-and somatostatin-expressing neurons in mice leads to distinct Rett syndrome-like phenotypes. Neuron 88, 651–658 (2015).
Krajnc, N. Management of epilepsy in patients with Rett syndrome: perspectives and considerations. Ther. Clin. Risk Manag. 11, 925–932 (2015).
Vignoli, A. et al. Effectiveness and tolerability of antiepileptic drugs in 104 girls with Rett syndrome. Epilepsy Behav. 66, 27–33 (2017).
Squillaro, T. et al. Reduced expression of MECP2 affects cell commitment and maintenance in neurons by triggering senescence: new perspective for Rett syndrome. Mol. Biol. Cell 23, 1435–1445 (2012).
Lee, B., Shin, D., Gross, S. P. & Cho, K. H. Combined positive and negative feedback allows modulation of neuronal oscillation frequency during sensory processing. Cell Rep. 25, 1548–1560 (2018).
Chen, G. et al. Distinct inhibitory circuits orchestrate cortical beta and gamma band oscillations. Neuron 96, 1403–1418 (2017).
Hashemi, E., Ariza, J., Rogers, H., Noctor, S. C. & Martinez-Cerdeno, V. The number of parvalbumin-expressing interneurons is decreased in the prefrontal cortex in autism. Cereb. Cortex 27, 1931–1943 (2017).
Thomson, J. A. et al. Embryonic stem cell lines derived from human blastocysts. Science 282, 1145–1147 (1998).
Tchieu, J. et al. Female human iPSCs retain an inactive X chromosome. Cell Stem Cell 7, 329–342 (2010).
Rousso, D. L., Gaber, Z. B., Wellik, D., Morrisey, E. E. & Novitch, B. G. Coordinated actions of the forkhead protein Foxp1 and Hox proteins in the columnar organization of spinal motor neurons. Neuron 59, 226–240 (2008).
Lee, B. et al. Dlx1/2 and Otp coordinate the production of hypothalamic GHRH- and AgRP-neurons. Nat. Commun. 9, 2026 (2018).
Kuwajima, T., Nishimura, I. & Yoshikawa, K. Necdin promotes GABAergic neuron differentiation in cooperation with Dlx homeodomain proteins. J. Neurosci. 26, 5383–5392 (2006).
Schindelin, J. et al. Fiji: an open-source platform for biological-image analysis. Nat. Methods 9, 676–682 (2012).
Butler, A., Hoffman, P., Smibert, P., Papalexi, E. & Satija, R. Integrating single-cell transcriptomic data across different conditions, technologies, and species. Nat. Biotechnol. 36, 411–420 (2018).
Stuart, T. et al. Comprehensive integration of single-cell data. Cell 177, 1888–1902 (2019).
Welch, J. D. et al. Single-cell multi-omic integration compares and contrasts features of brain cell identity. Cell 177, 1873–1887 (2019).
Yuste, R. et al. A community-based transcriptomics classification and nomenclature of neocortical cell types. Nat. Neurosci. 23, 1456–1468 (2020).
Krienen, F. M. et al. Innovations present in the primate interneuron repertoire. Nature 586, 262–269 (2020).
Mayer, C. et al. Developmental diversification of cortical inhibitory interneurons. Nature 555, 457–462 (2018).
Hodge, R. D. et al. Conserved cell types with divergent features in human versus mouse cortex. Nature 573, 61–68 (2019).
Gouwens, N. W. et al. Integrated morphoelectric and transcriptomic classification of cortical GABAergic. Cell 183, 935–953 (2020).
Polioudakis, D. et al. A single-cell transcriptomic atlas of human neocortical development during mid-gestation. Neuron 103, 785–801 (2019).
Cao, Y. et al. scDC: single-cell differential composition analysis. BMC Bioinformatics 20, 721 (2019).
Raudvere, U. et al. g:Profiler: a web server for functional enrichment analysis and conversions of gene lists. Nucleic Acids Res. 47, W191–W198 (2019).
Reimand, J., Kull, M., Peterson, H., Hansen, J. & Vilo, J. g:Profiler—a web-based toolset for functional profiling of gene lists from large-scale experiments. Nucleic Acids Res. 35, W193–W200 (2007).
Chen, T. W. et al. Ultrasensitive fluorescent proteins for imaging neuronal activity. Nature 499, 295–300 (2013).
We thank S. Butler, T. Carmichael and members of the laboratory of B.G.N. for helpful discussions and comments on the manuscript; N. Vishlaghi and F. Turcios-Hernandez for technical assistance, and J. Lee, S.-K. Lee, H. Shinagawa and K. Yoshikawa for valuable reagents. We also thank the UCLA Eli and Edythe Broad Stem Cell Research Center (BSCRC) and Intellectual and Developmental Disabilities Research Center microscopy cores for access to imaging facilities. This work was supported by grants from the California Institute for Regenerative Medicine (CIRM) (DISC1-08819 to B.G.N.), the National Institute of Health (R01NS089817, R01DA051897 and P50HD103557 to B.G.N.; K08NS119747 to R.A.S.; K99HD096105 to M.W.; R01MH123922, R01MH121521 and P50HD103557 to M.J.G.; R01GM099134 to K.P.; R01NS103788 to W.E.L.; R01NS088571 to J.M.P.; R01NS030549 and R01AG050474 to I.M.), and research awards from the UCLA Jonsson Comprehensive Cancer Center and BSCRC Ablon Scholars Program (to B.G.N.), the BSCRC Innovation Program (to B.G.N., K.P. and W.E.L.), the UCLA BSCRC Steffy Brain Aging Research Fund (to B.G.N. and W.E.L.) and the UCLA Clinical and Translational Science Institute (to B.G.N.), Paul Allen Family Foundation Frontiers Group (to K.P. and W.E.L.), the March of Dimes Foundation (to W.E.L.) and the Simons Foundation Autism Research Initiative Bridge to Independence Program (to R.A.S. and M.J.G.). R.A.S. was also supported by the UCLA/NINDS Translational Neuroscience Training Grant (R25NS065723), a Research and Training Fellowship from the American Epilepsy Society, a Taking Flight Award from CURE Epilepsy and a Clinician Scientist training award from the UCLA BSCRC. J.E.B. was supported by the UCLA BSCRC Rose Hills Foundation Graduate Scholarship Training Program. M.W. was supported by postdoctoral training awards provided by the UCLA BSCRC and the Uehara Memorial Foundation. O.A.M. and A.K. were supported in part by the UCLA-California State University Northridge CIRM-Bridges training program (EDUC2-08411). We also acknowledge the support of the IDDRC Cells, Circuits and Systems Analysis, Microscopy and Genetics and Genomics Cores of the Semel Institute of Neuroscience at UCLA, which are supported by the NICHD (U54HD087101 and P50HD10355701). We lastly acknowledge support from a Quantitative and Computational Biosciences Collaboratory Postdoctoral Fellowship to S.M. and the Quantitative and Computational Biosciences Collaboratory community, directed by M. Pellegrini.
The use of pifithrin compounds to treat Rett Syndrome and fusion organoids to screen for preclinical efficacy is covered by a patent application filed by the UC Regents with R.A.S., W.E.L. and B.G.N. as inventors. The remaining authors declare no competing interests.
Peer review information Nature Neuroscience thanks Benjamin Philpot and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended Data Fig. 1 Plots and table of batch and patient line variability for key experimental measures.
a, Plots of experimental results from different batches of iCtrl and Mut Cx+GE fusion organoids analyzed for the percentage of cells in the cortical compartment that expressed tdTomato (tdTom) after the GE portion was labeled with AAV1-CAG:tdTom virus (left panel) or GAD65 antibodies (right panel). Each dot represents an individual organoid section used for analysis and numbered elements on the x-axis represent individual experiments. No within- or across-genotype differences were noted for either percentage of Cx expressing tdTom or GAD65. b,c, Plots of individual experimental results from iCtrl and Mut Cx+GE fusion calcium indicator and LFP experiments. Each dot represents results from an independent experiment, numbered elements on the x-axis represent independent organoid batches. Blue dots represent hiPSC line I (Rett patient with a 705delG frameshift mutation), green dots represent hiPSC line II (Rett patient with 1461 A > G missense mutation), and orange and red circles indicate independently isolated hiPSC lines from the same patient. For calcium indicator and LFP data, plots were generated for all experiments in which statistically significant differences between Mut and iCtrl Cx+GE fusions were reported. In all cases in which the same measure resulted in statistically significant differences between Mut and iCtrl in both hiPSC patient lines, the two patient lines were combined for within genotype statistical analyses (for example, proportion of multispiking neurons). d, Table with mean, standard deviation (Std Dev), within genotype P value, and between genotype P value for all measures shown in a-c. The results show relatively low Std Dev within genotypes as reflected in non-significant P values, yet highly significant differences between the iCtrl and Mut groups in nearly all functional measurements. All between batch statistical analyses were by ANOVA. All between genotype analyses by ANOVA with correction for multiple comparisons by Tukey’s test, unless otherwise specified in the main text.
Extended Data Fig. 2 Constrained non-negative matrix factorization (CNMF) based Ca2+ data extraction workflow and output.
a, Raw image of an GCaMP6f infected Cx+GE organoid (left) and CNMF based identification of fluorescently active (spiking) GCaMP regions of interest (right). b-d, Identification and analysis of individual neuronal Ca2+ spiking data. b, Changes in GCaMP6f fluorescence (normalized ΔF/F) for each neuron in a displayed as individual spike trains (left) or the same data displayed as a colorized amplitude plot (right). Individual spiking data are then used to determine various measures of spiking behavior including overall synchronicity based on a threshold level determined following spike shuffling c and calculation of interspike intervals d. e, Simultaneous to b-d, Ca2+ spiking data are categorized into neuronal microcircuits (clusters) based on correlations between individual Ca2+ spikes. f, during initial analyses, alternative clustering approaches including cross-correlation was used and the neural microcircuits resulting from multiple approaches were compared to determine the optimal clustering paradigm.
Extended Data Fig. 3 Immunohistochemical analyses reveal similar cell composition in iCtrl and Mut fusion organoids.
a, Day ~100 iCtrl and Mut Cx+GE fusion organoids have comparable numbers of GAD65+ positive cells in both the GE and Cx end (quantification in Fig. 3c). b, Both unfused Mut and unfused iCtrl day ~100 GE organoids contain multiple interneuron subtypes including CALRETININ, CALBINDIN, and SOMATOSTATIN (SST) expressing cells. c, Mut and iCtrl Day ~100 GE and Cx organoids also contain GFAP+ astrocytes. All images are representative examples from 3 or more independently imaged sections. See Supplementary Table 4 for additional details.
Extended Data Fig. 4 Rett syndrome fusion organoids from a second patient hiPSC line exhibit neural network irregularities in calcium indicator measurements.
a, Immunohistochemical analyses of isogenic Cx and GE organoids from a second Rett syndrome patient hiPSC line (harboring a 1461 A > G missense mutation, indicated by “II”) reveals either the presence (iCtrl-II) or absence (Mut-II) of MECP2 expression. Representative images from n = 2 independent experiments and 6 imaged sections. b, Mut-II Cx+GE fusions contain hyperexcitable neurons as indicated by the red boxed regions in the bottom ΔF/F colorized amplitude plot and spike plot. These plots show trains of repeatedly firing Ca2+ transients with short interspike intervals that are not present in iCtrl-II Cx+GE (top plots). c, There is no discernible change in synchronization of calcium transients between Mut and iCtrl as reflected in the clustergrams. d, The hyperexcitable phenotype in Mut-II Cx+GE fusions is reflected in the pooled data both by significant increases in multispiking neurons and decreases in mean and median interpeak intervals. Pooled data quantifications, n = 10 iCtrl-II and n = 6 Mut-II fusion organoids, where each n is an independently generated organoid. Two-sided Mann-Whitney tests were used, *P = 0.0071 for the proportion of multispiking neurons, **P = 0.0047 for the mean interspike interval, **P = 0.0017 for the median interspike interval, ns = not significant. Plot in d displays the full distribution of individual data points with dotted lines indicating the median and quartile values.
Extended Data Fig. 5 Enrichment of autism and epilepsy risk genes in up/downregulated genes in MECP2 mutant and isogenic control organoids.
a, Overlap of differentially expressed genes in MECP2 mutant organoids (all cell groups) with SFARI autism spectrum disorder (ASD) gene categories 1-3 and DisGeNET epilepsy Gene-Disease Association list (CUI: C0014544). Overlaps between data are indicated by red and green shading and displayed as Venn diagrams in b. c, Two-sided Fisher’s Exact Test was used to determine if Up/Downregulated genes show enrichment for genes in SFARI and epilepsy gene lists. Odds ratio from the test are displayed along with Bonferroni-corrected P values. Up/Epilepsy: ***P = 0.0016, Down/Epilepsy: ****P = 1.81×10-5, Up/ASD: ****P = 5.72×10-9, Down/ASD: P = 1.00.
Extended Data Fig. 6 UMAP representation of select genes associated with synaptogenesis and kainate responsivity.
a, UMAP representation of select genes associated with axonal projections and synaptogenesis found to be upregulated in MECP2 mutant Cx+GE fusion organoids. Violin plots display the relative expression level of each gene across the indicated cell clusters. b, UMAP representation of kainate receptor gene expression within the Cx+GE fusion organoids.
Top 10 most enriched Gene Ontology biological process (GO BP) terms associated with upregulated or downregulated differentially expressed genes when comparing Mut and iCtrl within the main excitatory (CPN and CFuPN) and interneuron (IN) clusters. Upregulated genes in the excitatory clusters are highly enriched for terms associated with synaptogenesis and axonal morphogenesis while downregulated genes are associated with mRNA catabolism and translation. In contrast, synaptogenesis terms are absent among the upregulated genes in the IN cluster, with this set populated by terms associated with forebrain differentiation and axonal morphogenesis. Downregulated genes in the IN cluster are enriched for metabolism and cellular cytoskeleton associated terms.
Extended Data Fig. 8 Spatially restricted microcircuit clusters and fewer synchronous events in MECP2 Mut Cx + GE organoids.
a, Pooled data for neuronal clusters derived here using Ca2+ activity correlations, reveal spatially restricted (smaller) microcircuit clusters with fewer average neurons per cluster in Mut compared to iCtrl. b, Pooled data of synchronous events demonstrates a reduced number of events, but with each event having a significantly higher amplitude (Fig. 6), in Mut compared to iCtrl. Synchronous events have similar overall duration in both conditions (n = 6 for iCtrl, n = 7 for Mut and represents independently generated organoids, *P = 0.0436 for Pairwise Distances, *P = 0.0203 for Cluster Circumference, *P = 0.0321 for Cluster Area, **P = 0.0089 for Neurons per Cluster, and *P = 0.0180 for Number of Synchronized Transients). Plots display the full distribution of individual data points with dotted lines to indicate the median and quartile values. Following a normality test, statistical significance was determined using a two-sided Mann-Whitney U-test.
a,d, Representative raw 10-minute LFP traces (top) and time expanded segments (bottom) from either unmixed iCtrl or Mut Cx+GE fusion organoids, or Mut Cx+iCtrl GE or iCtrl Cx+Mut GE mixed fusion organoids. b,e, Morlet plots derived from the time expanded segments shown in a,d. c,f, Periodogram derived from the entire 10 min traces shown in a,d.
Extended Data Fig. 10 Rett syndrome fusion organoids from a second patient hiPSC line demonstrate epileptiform changes in extracellular recordings.
a, Raw trace of a representative 10-minute LFP recording (top) and time expanded window (bottom) from iCtrl-II, Mut-II, or Mut-II + PFT-α Cx+GE fusion organoids. b, Morlet plots showing high frequency activity associated with the time expanded segments shown in (a). (c) Periodograms derived from the entire recordings shown in a. d, Quantification of high and low gamma spectral power from LFP recordings demonstrates a significant decrease in low gamma power and a sizeable but non-significant loss of high gamma power in Mut-II Cx+GE fusions. PFT-α treatment of Mut-II Cx+GE fusions results in a statistically significant rescue of both low and high gamma oscillatory power. Low gamma; Ordinary ANOVA, overall P = 0.0024, Tukey’s Multiple comparisons, *P = 0.0313 iCtrl II vs Mut II, *P = 0.0211 Mut II vs Mut II + PFT. High gamma; Ordinary ANOVA, overall P = 0.0091, Tukey’s multiple comparisons, *P = 0.0243 Mut II vs Mut II + PFT, P = 0.09 between iCtrl-II and Mut. e, Spike frequency across multiple independent experiments Kruskal-Wallis test, overall P = 0.0003, Dunn’s multiple comparisons **P = 0.0028, *P = 0.0276. For d and e, n = 5 for iCtrl-II and Mut-II + PFT-α, n = 6 for Mut-II (total n = 16). f, Plots of high and low gamma spectral power versus spike frequency demonstrates an inverse relationship between gamma power and spiking. The solid black line is the best fit following linear regression, and the dashed magenta lines indicate 95% confidence intervals for the estimated line of best fit. The slope of the line of best fit is indicated above each graph. Plots in d and e display the full distribution of individual data points with dotted lines to indicate the median and quartile values.
Supplementary Figs. 1–5 and Supplementary Table 4
Live two-photon microscopic imaging of neural activities within a representative Cx + GE fusion organoid. D90 H9 hESC-derived Cx + GE fusion organoids were infected with AAV1-GCaMP6f and imaged 12 d later (D102) using two-photon confocal microscopy.
CNMF-E-based evaluation of calcium activities within a Cx + GE fusion organoid. The video demonstrates real-time translation of changes in GCaMP6f fluorescence shown in Supplementary Video 1 into peaks of activity used in subsequent analyses. Neurons demonstrating activity are identified and numbered on the left and normalized ΔF/F values for each neuron are plotted on the right.
Post hoc clustering of calcium activity. An example demonstrating the segregation of neurons based on calcium activity into microcircuit clusters. The clusters in this example are based on correlated calcium transients between individual neurons. The rows of neurons on the right represent most neurons in each cluster and are color coded. Each cluster’s calcium activity (color matched to the right) is plotted as ΔF/F values on the left. This example is from the same H9 hESC-derived Cx + GE fusion organoid shown in Supplementary Videos 1 and 2.
Activity profile of a representative Cx + GE fusion organoid before exposure to BMI. This video displays the baseline GCaMP6f activity profile of a D99 H9 hESC-derived Cx + GE fusion organoid immediately before addition of 100 μM of the GABAA receptor antagonist BMI.
Calcium transient synchrony after BMI administration to a representative Cx + GE fusion organoid. This video displays changes in the neural network activities of the Cx + GE fusion organoid shown in Supplementary Video 4 approximately 1 min after the addition of 100 μM BMI. Note the repeated synchronization of calcium transients across the organoid.
Neural network activity of a representative Cx + GE fusion organoid immediately before the addition of gabazine. This video displays the baseline calcium transients present in a D98 H9 hESC-derived Cx + GE fusion organoid immediately before addition of 25 μM of the GABAA receptor antagonist gabazine.
Neural network activity of a representative Cx + GE fusion organoid immediately after the addition of gabazine. This video displays the prominent synchronization of neuronal activities seen in the D98 Cx + GE fusion organoid shown in Supplementary Video 6 approximately 1 min after addition of 25 μM gabazine.
Calcium activity in an iCtrl Cx + GE fusion organoid. A representative example of live two-photon confocal imaging of GCaMP6f fluorescence from a D103 iCtrl hiPSC-derived Cx + GE fusion organoid.
Spontaneous synchronizations of calcium transients in an MECP2-mutant Cx + GE fusion organoid. A representative example of the abnormal synchronizations of calcium transients seen in D103 Mut hiPSC-derived Cx + GE fusion organoids.
Calcium activity in an iCtrl Cx + GE fusion organoid created from hiPSCs from the second individual with Rett syndrome. A representative example of live two-photon confocal imaging of GCaMP6f fluorescence within a D100 iCtrl hiPSC-derived Cx + GE fusion organoid generated from hiPSCs derived from a second individual with Rett syndrome.
Hyperexcitable calcium indicator activity in an MECP2-mutant Cx + GE fusion organoid created from hiPSCs from the second individual with Rett syndrome. A representative example of hyperexcitable calcium indicator activity seen in D103 Mut hiPSC-derived Cx + GE fusion organoids. The yellow arrows indicate examples of hyperexcitable neurons resulting in reduced inter-peak intervals between activations. This is representative of the calcium indicator activity seen in Mut Cx + GE organoids generated from hiPSCs from the second individual with Rett syndrome.
Calcium activity in a mixed Mut Cx and iCtrl GE (Mut Cx + iCtrl GE) fusion organoid. A representative example of live two-photon confocal imaging of GCaMP6f fluorescence from a D101 mixed Mut Cx + iCtrl GE hiPSC-derived fusion organoid.
Spontaneous synchronizations of calcium transients in a mixed iCtrl Cx and MECP2-mutant GE (iCtrl Cx + Mut GE) fusion organoid. A representative example of the abnormal synchronizations of calcium transients seen in ~D100 mixed iCtrl Cx + Mut GE hiPSC-derived fusion organoids. This example is from a D102 fusion organoid.
About this article
Cite this article
Samarasinghe, R.A., Miranda, O.A., Buth, J.E. et al. Identification of neural oscillations and epileptiform changes in human brain organoids. Nat Neurosci (2021). https://doi.org/10.1038/s41593-021-00906-5